Prediction of Agriculture Yieldsusing Machine Learning Algorithm (Turkish Journal of Computer and Mathematics Education (TURCOMAT), 2022)
In recent years, great efforts have been carried out on the challenging task of predictingdifferent crop yields. Developing exact models for crop yield estimation utilizing Information andCommunication Technologies may support farmers and different stakeholders to improve decisionmaking about national food import/export and food security. Most of the crops are selected based onthe economic range. In our proposed work also we have consider the economical crops and theyprovide better prediction compared with the existing classifiers. The proposed ensemble classifierprovides an efficient crop yield and crop disease forecasting model. Our proposed work providesknowledge to the farmers about the climatic conditions of the probability of crop disease and theclimatic conditions for better crop yield. Even it discovers the crop yield and crop diseases, but doesnot concentrate on the solution to solve the productivity issue caused by crop diseases. Further, ourfuture work concentrates on the above issue with different algorithms.